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Computing features

--- a/dnn/denoise.c

+++ b/dnn/denoise.c

@@ -64,7 +64,7 @@

 #define CEPS_MEM 8

 #define NB_DELTA_CEPS 6

-#define NB_FEATURES (NB_BANDS+3*NB_DELTA_CEPS+2)

+#define NB_FEATURES (2*NB_BANDS+2+LPC_ORDER)

 #ifndef TRAINING

@@ -305,12 +305,11 @@

 int band_lp = NB_BANDS;

 #endif

-static void frame_analysis(DenoiseState *st, kiss_fft_cpx *X, float *Ex, const float *in) {

+static void frame_analysis(DenoiseState *st, float *lpc, kiss_fft_cpx *X, float *Ex, const float *in) {

   int i;

   float x[WINDOW_SIZE];

   float x0[WINDOW_SIZE];

   float ac[LPC_ORDER+1];

-  float lpc[LPC_ORDER];

   float rc[LPC_ORDER];

   RNN_COPY(x, st->analysis_mem, FRAME_SIZE);

   for (i=0;i<FRAME_SIZE;i++) x[FRAME_SIZE + i] = in[i];

@@ -360,17 +359,15 @@

                                   float *Ex, float *Ep, float *Exp, float *features, const float *in) {

   int i;

   float E = 0;

-  float *ceps_0, *ceps_1, *ceps_2;

-  float spec_variability = 0;

   float Ly[NB_BANDS];

+  float lpc[LPC_ORDER];

   float p[WINDOW_SIZE];

   float pitch_buf[PITCH_BUF_SIZE];

   int pitch_index;

   float gain;

-  float *(pre[1]);

   float tmp[NB_BANDS];

   float follow, logMax;

-  frame_analysis(st, X, Ex, in);

+  frame_analysis(st, lpc, X, Ex, in);

   RNN_MOVE(st->pitch_buf, &st->pitch_buf[FRAME_SIZE], PITCH_BUF_SIZE-FRAME_SIZE);

   RNN_COPY(&st->pitch_buf[PITCH_BUF_SIZE-FRAME_SIZE], in, FRAME_SIZE);

   //pre[0] = &st->pitch_buf[0];

@@ -378,14 +375,14 @@

   pitch_downsample(pitch_buf, PITCH_BUF_SIZE);

   pitch_search(pitch_buf+PITCH_MAX_PERIOD, pitch_buf, PITCH_FRAME_SIZE<<1,

                (PITCH_MAX_PERIOD-3*PITCH_MIN_PERIOD)<<1, &pitch_index);

-  printf("%d ", pitch_index);

+  //printf("%d ", pitch_index);

   pitch_index = 2*PITCH_MAX_PERIOD-pitch_index;

-  printf("%d ", pitch_index);

+  //printf("%d ", pitch_index);

   gain = remove_doubling(pitch_buf, 2*PITCH_MAX_PERIOD, 2*PITCH_MIN_PERIOD,

           2*PITCH_FRAME_SIZE, &pitch_index, st->last_period, st->last_gain);

   st->last_period = pitch_index;

   st->last_gain = gain;

-  printf("%d %f\n", pitch_index, gain);

+  //printf("%d %f\n", pitch_index, gain);

   for (i=0;i<WINDOW_SIZE;i++)

     p[i] = st->pitch_buf[PITCH_BUF_SIZE-WINDOW_SIZE-pitch_index/2+i];

   apply_window(p);

@@ -393,60 +390,36 @@

   compute_band_energy(Ep, P);

   compute_band_corr(Exp, X, P);

   for (i=0;i<NB_BANDS;i++) Exp[i] = Exp[i]/sqrt(.001+Ex[i]*Ep[i]);

+#if 0

+  for (i=0;i<NB_BANDS;i++) printf("%f ", Exp[i]);

+  printf("\n");

+#endif

   dct(tmp, Exp);

-  for (i=0;i<NB_DELTA_CEPS;i++) features[NB_BANDS+2*NB_DELTA_CEPS+i] = tmp[i];

-  features[NB_BANDS+2*NB_DELTA_CEPS] -= 1.3;

-  features[NB_BANDS+2*NB_DELTA_CEPS+1] -= 0.9;

-  features[NB_BANDS+3*NB_DELTA_CEPS] = .01*(pitch_index-300);

+  for (i=0;i<NB_BANDS;i++) features[NB_BANDS+i] = tmp[i];

+  features[NB_BANDS] -= 1.3;

+  features[NB_BANDS+1] -= 0.9;

   logMax = -2;

   follow = -2;

   for (i=0;i<NB_BANDS;i++) {

     Ly[i] = log10(1e-2+Ex[i]);

-    Ly[i] = MAX16(logMax-7, MAX16(follow-1.5, Ly[i]));

+    Ly[i] = MAX16(logMax-8, MAX16(follow-2.5, Ly[i]));

     logMax = MAX16(logMax, Ly[i]);

-    follow = MAX16(follow-1.5, Ly[i]);

+    follow = MAX16(follow-2.5, Ly[i]);

     E += Ex[i];

   }

-  if (!TRAINING && E < 0.04) {

-    /* If there's no audio, avoid messing up the state. */

-    RNN_CLEAR(features, NB_FEATURES);

-    return 1;

-  }

   dct(features, Ly);

-  features[0] -= 12;

-  features[1] -= 4;

-  ceps_0 = st->cepstral_mem[st->memid];

-  ceps_1 = (st->memid < 1) ? st->cepstral_mem[CEPS_MEM+st->memid-1] : st->cepstral_mem[st->memid-1];

-  ceps_2 = (st->memid < 2) ? st->cepstral_mem[CEPS_MEM+st->memid-2] : st->cepstral_mem[st->memid-2];

-  for (i=0;i<NB_BANDS;i++) ceps_0[i] = features[i];

-  st->memid++;

-  for (i=0;i<NB_DELTA_CEPS;i++) {

-    features[i] = ceps_0[i] + ceps_1[i] + ceps_2[i];

-    features[NB_BANDS+i] = ceps_0[i] - ceps_2[i];

-    features[NB_BANDS+NB_DELTA_CEPS+i] =  ceps_0[i] - 2*ceps_1[i] + ceps_2[i];

-  }

-  /* Spectral variability features. */

-  if (st->memid == CEPS_MEM) st->memid = 0;

-  for (i=0;i<CEPS_MEM;i++)

-  {

-    int j;

-    float mindist = 1e15f;

-    for (j=0;j<CEPS_MEM;j++)

-    {

-      int k;

-      float dist=0;

-      for (k=0;k<NB_BANDS;k++)

-      {

-        float tmp;

-        tmp = st->cepstral_mem[i][k] - st->cepstral_mem[j][k];

-        dist += tmp*tmp;

-      }

-      if (j!=i)

-        mindist = MIN32(mindist, dist);

-    }

-    spec_variability += mindist;

-  }

-  features[NB_BANDS+3*NB_DELTA_CEPS+1] = spec_variability/CEPS_MEM-2.1;

+  features[0] -= 4;

+#if 0

+  for (i=0;i<NB_BANDS;i++) printf("%f ", Ly[i]);

+  printf("\n");

+#endif

+  features[2*NB_BANDS] = .01*(pitch_index-200);

+  features[2*NB_BANDS+1] = gain;

+  for (i=0;i<LPC_ORDER;i++) features[2*NB_BANDS+2+i] = lpc[i];

+#if 0

+  for (i=0;i<NB_FEATURES;i++) printf("%f ", features[i]);

+  printf("\n");

+#endif

   return TRAINING && E < 0.1;

 }

-- 

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